Every engineering organisation has its stories.
Nobody is ever entirely sure whether these are:
Over the last few posts, I’ve been writing about AI from a fairly close range — how it changes engineering teams, delivery dynamics, capability development, and the shape of organisations.
In other words, the micro view — what happens inside teams when capability, speed, and decision-making all shift at once.
But the more I’ve thought about it, the harder it’s becoming to ignore the bigger picture, as the same forces are playing out at a much larger scale.
Most discussions about AI focus on capability — what it can do, how fast it's improving, and where it might go next.
My last post focused on the fact that less attention is paid to something more subtle, but arguably more disruptive.
Time.
Not just in the sense of speed, but in how time is experienced across different parts of a system.
Because one of the emerging challenges is that time is no longer behaving consistently.
In my most recent posts, I’ve explored how AI is starting to reshape both the structure of engineering teams and the shape of individual capability.
There’s a third dimension that sits across both: Time.
In my last post, I explored the idea that we may be moving from a knowledge-based economy towards something that places greater emphasis on judgement, framing, and leverage.
That shift doesn’t just affect individuals. It has implications for how we structure teams, how we develop capability, and how we think about the long-term sustainability of engineering organisations.